QA Engineer - Data Quality & Test Automation

We are looking for a talented QA Engineer - Data Quality & Test Automation to join our Data Services team. The ideal candidate will have strong experience in data quality validation, test automation, Python, SQL, data reconciliation, and data workflow testing. This role requires a strong QA mindset with the ability to design comprehensive test strategies, create automated test suites, validate large datasets, identify data-quality issues, and ensure that data products and pipelines meet business requirements.

The successful candidate will be a strong analytical thinker who can work closely with Data Engineers, Data Scientists, Analysts, and business stakeholders to improve solution quality and testability.

Key Responsibilities:

• Develop and implement test strategies, test plans, and QA engineering practices for data-intensive applications and data products.
• Design and execute both manual and automated testing, with a strong focus on data quality and validation.
• Build robust automated test suites, test scripts, use cases, and validation frameworks.
• Develop test scenarios capable of identifying data defects, transformation issues, pipeline failures, and business-rule inconsistencies.
• Perform comprehensive data validation using SQL and Python.
• Validate data transformations, ETL/ELT workflows, data pipelines, and downstream datasets.
• Perform source-to-target data reconciliation and investigate data mismatches.
• Generate, manage, and maintain test datasets required for functional, regression, integration, and data-quality testing.
• Configure and maintain appropriate test environments and test configurations.
• Test data workflows involving large datasets and identify performance or scalability-related issues.
• Validate Power BI reports and dashboards, including data accuracy, calculations, filters, aggregations, and business rules.
• Create and maintain automated data-quality checks and validation frameworks.
• Define and track quality metrics for data pipelines, data products, and customer deliverables.
• Identify defects, document them accurately, assign appropriate severity/priority, and track them through successful resolution.
• Perform root-cause analysis of data-quality issues and collaborate with engineering teams on corrective actions.
• Work closely with Data Engineers, Data Scientists, and Data Analysts to ensure solutions are designed with testability and quality in mind.
• Participate in requirements and solution-design discussions and identify potential quality risks early in the development lifecycle.
• Conduct regression, integration, functional, system, and end-to-end testing.
• Research and evaluate new QA technologies, automation frameworks, and data-quality tools.
• Continuously improve test coverage, automation, quality processes, and engineering practices.

Required Technical Skills:

• Strong Python programming and scripting skills.
• Experience developing automated test frameworks and scripts.
• Proven experience with programmatic testing of software/data products.
• Strong understanding of automation concepts, reusable test components, and regression testing.
• Strong SQL fundamentals with the ability to write complex SQL queries for data validation and reconciliation.
• Strong understanding of data quality principles and experience with data reconciliation and data workflows.
• Experience testing ETL/ELT pipelines and data processing workflows.
• Familiarity with Jira or other defect/issue tracking systems, and exposure to CI/CD-based automated testing is an advantage.

Qualifications:

• 3+ years of experience in Quality Assurance, with at least 2+ years in test automation and data validation.
• Strong hands-on experience with Python and SQL.
• Experience testing data workflows and performing data reconciliation.
• Strong analytical, critical-thinking, and problem-solving skills.
• Excellent collaboration and communication skills.

What we offer:

• Opportunity to work in a dynamic team environment with a focus on innovation.
• Engagement in challenging projects that enhance your skills and career growth.
• Supportive culture that values collaboration and continuous improvement.